CN113469980B - Flange identification method based on image processing - Google Patents
Flange identification method based on image processing Download PDFInfo
- Publication number
- CN113469980B CN113469980B CN202110776870.8A CN202110776870A CN113469980B CN 113469980 B CN113469980 B CN 113469980B CN 202110776870 A CN202110776870 A CN 202110776870A CN 113469980 B CN113469980 B CN 113469980B
- Authority
- CN
- China
- Prior art keywords
- flange
- image
- total
- roundness
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012545 processing Methods 0.000 title claims abstract description 34
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000004364 calculation method Methods 0.000 claims description 27
- 230000000877 morphologic effect Effects 0.000 claims description 16
- 125000004122 cyclic group Chemical group 0.000 claims description 4
- 238000012216 screening Methods 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 3
- 230000035945 sensitivity Effects 0.000 claims description 3
- 238000001514 detection method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 210000001503 joint Anatomy 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/2408—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures for measuring roundness
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/155—Segmentation; Edge detection involving morphological operators
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30164—Workpiece; Machine component
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Quality & Reliability (AREA)
- Image Analysis (AREA)
Abstract
The invention relates to the technical field of computer vision, and particularly discloses a flange identification method based on image processing, which comprises the following steps: obtaining a flange image to be identified, obtaining a plurality of target flange contours after processing, and further obtaining a plurality of fitted target flange elliptical contours; circularly calculating the total roundness values of a plurality of fitted target flange elliptical profiles, and continuously updating the minimum total roundness value; and when the circulation is performed for a certain number of times, selecting the final updated total roundness minimum value, obtaining the corresponding fitted target flange elliptical profile according to the minimum total roundness value, and displaying the fitted target flange elliptical profile corresponding to the minimum total roundness value on the flange image to be identified to obtain a flange identification result. The method solves the problem of flange identification in the coarse positioning of the intelligent oil delivery arm, has good universality and higher identification rate.
Description
Technical Field
The invention relates to the technical field of computer vision, in particular to a flange identification method based on image processing.
Background
With the increasing degree of industrial automation, more and more labor is replaced by machines. The traditional offshore oil delivery arm is in butt joint with a flange on a ship in a manual remote control mode, so that the efficiency is not high enough, and high labor cost is born. The appearance of intelligent oil delivery arm has realized its automatic butt joint with the flange, has reduced the human cost and has improved efficiency to will become the important component part of wisdom pier. The development of computer and other technologies makes the application of visual positioning wider and wider, and according to the application scene, a binocular positioning method is selected, and the flange recognition success rate directly influences the positioning result.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides the flange identification method based on image processing, which solves the problem of flange identification in the rough positioning of the intelligent oil delivery arm.
As a first aspect of the present invention, there is provided an image processing-based flange recognition method including:
step S1: acquiring a flange image to be identified;
step S2: processing the flange image to be identified to obtain a processed flange image;
step S3: performing image binarization processing on the processed flange image to obtain a binarized image;
step S4: performing morphological operation on the binarized image to obtain a flange image after morphological operation;
step S5: screening all contours in the flange image after morphological operation to obtain a plurality of target flange contours;
step S6: respectively carrying out ellipse fitting on a plurality of target flange profiles to obtain a plurality of fitted target flange ellipse profiles;
step S7: circularly calculating the total roundness value s of the plurality of fitted target flange elliptical profiles, and setting in advanceDetermining a total roundness minimum s min Updating the total roundness minimum s according to the cyclic calculation result min ；
Step S8: judging whether the calculated number i of the total roundness value S is larger than or equal to the total calculated number M, when the calculated number i is smaller than the total calculated number M, adding 1 to the calculated number i, returning to the step S3 by adding 1 to start cyclic calculation of the total roundness value S, and continuously updating the total roundness minimum value S min Until the calculated times i is more than or equal to the calculated times M; when the total calculated number M is greater than or equal to the total roundness minimum value s updated last is selected min The corresponding minimum total roundness value S, the corresponding fitted target flange elliptical profile is obtained according to the minimum total roundness value S, and step S9 is executed;
step S9: and displaying the fitted target flange ellipse outline corresponding to the minimum total roundness value s on the flange image to be identified to obtain a flange identification result.
Further, the step S2 further includes:
performing median filtering treatment on the flange image to be identified to obtain a filtered flange image;
and converting the filtered flange image into a gray image.
Further, the steps S3 and S4 further include:
performing image binarization processing on the gray level image to obtain a binarized image;
and sequentially performing a closing operation and an opening operation on the binarized image to obtain the flange image after morphological operation.
Further, the method further comprises the following steps:
judging whether the filtered flange image is a gray image or not;
if the filtered flange image is a color image, the filtered flange image is first grayed, and the graying formula is Gray (i, j) =ar (i, j) +bg (i, j) +cb (i, j), wherein Gray represents a value after graying of a pixel point, R, G, B represents color component values of red, green and blue on the corresponding pixel, a, b and c are weights of red, green and blue respectively, and herein a, b and c are standard values according to the sensitivity degree of human eyes, and are respectively 0.299, 0.578 and 0.114;
and if the filtered flange image is a gray image, directly performing image binarization processing.
Further, the step S3 further includes:
setting the initial threshold of image binarization as 0, wherein the formula of image binarization is as follows:
where T represents a threshold, the formula for binarizing the image means that pixels above the threshold are set to be brightest and pixels below the threshold are set to be darkest.
Further, in the step S6, the method further includes:
and respectively carrying out ellipse fitting on a plurality of target flange profiles by adopting a least square method to obtain a plurality of fitted target flange ellipse profiles.
Further, the step S7 further includes:
respectively calculating the roundness value of each fitted target flange elliptical contour, and calculating the total roundness value s of the plurality of fitted target flange elliptical contours according to the roundness value of each fitted target flange elliptical contour;
calculating the roundness value of each fitted target flange elliptical profile through the formula c=b/a, wherein a represents the major half axis of the ellipse, b represents the minor half axis of the ellipse, and the calculation formula of the total roundness value s of all fitted target flange elliptical profiles is:
wherein C is 1 ，C 2 ，...，C n Respectively representing the roundness value of each fitted target flange elliptical profile, and n represents the judgment of the target methodThe number of the blue oval contours is normally not greater than 1, so that the total roundness value s is the minimum value s min The initial value of (1) is set to be 1, and the currently calculated total roundness value s and the total roundness minimum value s are calculated min In comparison with s min S > s, then assign s to s min To update the total roundness minimum s min 。
Further, in the step S8, the method further includes:
when the calculated number i of the total roundness values S is smaller than the total calculated number M, the calculated number i is increased by 1, the step S3 is returned to by the calculated number i plus 1, the total roundness values S of all the fitted target flange elliptical profiles are calculated again, and if the calculated total roundness values S are smaller than the updated total roundness minimum values S in the last calculation, the calculated total roundness values S are calculated again min The calculated total roundness value s is continuously assigned to the minimum value s of the total roundness min To continue to update the total roundness minimum s min The updated total roundness minimum s will be continued min And in the next calculation of the total roundness value s, the calculated number i is equal to or greater than the total calculated number M.
Further, the step S1 further includes: and acquiring a flange image to be identified by adopting a high-definition camera.
The flange identification method based on image processing provided by the invention has the following advantages: the method is applied to the intelligent oil delivery arm, and has higher recognition rate and accuracy rate for the flange on the ship.
Drawings
The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate the invention and together with the description serve to explain, without limitation, the invention.
Fig. 1 is a flowchart of a flange identification method based on image processing.
Fig. 2 is a schematic diagram of an image of a flange to be identified according to the present invention.
Fig. 3 is a schematic diagram of a flange identification result provided by the invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following is a detailed description of specific implementation, structure, characteristics and effects of the flange identification method based on image processing according to the invention with reference to the accompanying drawings and preferred embodiments. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
In this embodiment, there is provided an image processing-based flange identification method, as shown in fig. 1, including:
step S1: acquiring a flange image to be identified, as shown in fig. 2;
step S2: processing the flange image to be identified to obtain a processed flange image;
step S3: performing image binarization processing on the processed flange image to obtain a binarized image;
step S4: performing morphological operation on the binarized image to obtain a flange image after morphological operation;
step S5: screening all contours in the flange image after morphological operation to obtain a plurality of target flange contours;
step S6: respectively carrying out ellipse fitting on a plurality of target flange profiles to obtain a plurality of fitted target flange ellipse profiles;
step S7: circularly calculating the total roundness value s of the plurality of fitted target flange elliptical profiles, and setting the minimum value s of the total roundness in advance min Updating the total roundness minimum s according to the cyclic calculation result min ；
Step S8: judging whether the calculated number of times i of the total roundness value S is larger than or equal to the total calculated number of times M, when the calculated number of times i is smaller than the total calculated number of times M, adding 1 to the calculated number of times i, returning to the step S3, starting to circularly calculate the total roundness value S,and continuously updating the total roundness minimum s min Until the calculated times i is more than or equal to the calculated times M; when the total calculated number M is greater than or equal to the total roundness minimum value s updated last is selected min The corresponding minimum total roundness value S, the corresponding fitted target flange elliptical profile is obtained according to the minimum total roundness value S, and step S9 is executed;
step S9: and displaying the fitted target flange ellipse outline corresponding to the minimum total roundness value s on the flange image to be identified to obtain a flange identification result, such as a black filling part shown in fig. 3.
Preferably, in the step S2, further includes:
performing median filtering treatment on the flange image to be identified to obtain a filtered flange image;
and converting the filtered flange image into a gray image.
It should be noted that in the process of acquiring the flange image to be identified, unnecessary interference information is inevitably generated, the quality of the image is greatly influenced, and the processing result of the image is possibly greatly influenced.
Preferably, in said steps S3 and S4, further comprises:
performing image binarization processing on the gray level image to obtain a binarized image;
and sequentially performing a closing operation and an opening operation on the binarized image to obtain the flange image after morphological operation.
It should be noted that some tiny holes and some burrs may exist in the binarized image, the binarized image is subjected to a closing operation to fill the tiny holes, and then is subjected to an opening operation to remove burrs on the edge, so that a flange image after morphological operation is obtained, and the flange can be better identified.
Preferably, the method further comprises:
judging whether the filtered flange image is a gray image or not;
if the filtered flange image is a color image, the filtered flange image is first grayed, and the graying formula is Gray (i, j) =ar (i, j) +bg (i, j) +cb (i, j), wherein Gray represents a value after graying of a pixel point, R, G, B represents color component values of red, green and blue on the corresponding pixel, a, b and c are weights of red, green and blue respectively, and herein a, b and c are standard values according to the sensitivity degree of human eyes, and are respectively 0.299, 0.578 and 0.114;
and if the filtered flange image is a gray image, directly performing image binarization processing.
Preferably, in the step S3, further includes:
setting the initial threshold of image binarization as 0, wherein the formula of image binarization is as follows:
where T represents a threshold, the formula for binarizing the image means that pixels above the threshold are set to be brightest and pixels below the threshold are set to be darkest.
The gray image was binarized starting with 0 as the threshold value.
It should be noted that, all contours in the flange image after morphological operation are screened, and the too large or too small contours are removed through size limitation so as to obtain a plurality of target flange contours; specifically, the contour detection and screening are performed on the flange image after morphological operation, and the contour detection of the binarized image is performed, namely, the contour of each connected domain is found. The area size range of the flange in the image can be determined according to the size of the flange on the ship and the distance range of the flange to the oil conveying arm, and the contours which are not necessarily the flange can be eliminated according to the area size range, so that the contours which are possibly the flange can be screened out.
Preferably, in the step S6, further includes:
and respectively carrying out ellipse fitting on a plurality of target flange profiles by adopting a least square method to obtain a plurality of fitted target flange ellipse profiles.
It should be noted that, because the flange plane and the camera plane have certain angles, the photographed flange is not a perfect circle but is very close to the circle, so that the ellipse fitting is performed on each screened target flange contour by using the least square method, and the fitted target flange ellipse contour is obtained.
It should be noted that, when the ellipse is fitted, the circle center and the radius can be obtained from the ellipse fitting algorithm, and the result can be drawn, and the ellipse fitting algorithm is an existing algorithm and is a conventional technology known to those skilled in the art, and is not described herein.
Preferably, in the step S7, further includes:
respectively calculating the roundness value of each fitted target flange elliptical contour, and calculating the total roundness value s of the plurality of fitted target flange elliptical contours according to the roundness value of each fitted target flange elliptical contour;
calculating the roundness value of each fitted target flange elliptical profile through the formula c=b/a, wherein a represents the major half axis of the ellipse, b represents the minor half axis of the ellipse, and the calculation formula of the total roundness value s of all fitted target flange elliptical profiles is:
wherein C is 1 ，C 2 ，...，C n Respectively representing the roundness value of each fitted target flange elliptical contour, wherein n represents the number of the determined target flange elliptical contours, and the total roundness value s is not larger than 1 under normal conditions, so that the total roundness minimum value s is obtained min The initial value of (1) is set to be 1, and the currently calculated total roundness value s and the total roundness minimum value s are calculated min In comparison with s min S > s, then assign s to s min To update the total roundness minimum s min 。
It should be noted that, by limiting the value of the roundness value of each fitted target flange ellipse contour to exclude the contour that is unlikely to be a flange, the non-flange portion in the image after morphological operation processing is almost effectively removed because the flange is very close to a circle in the image, and a plurality of flanges may exist in one image, so the above formula is used to determine the total roundness value s of all fitted target flange ellipse contours on one image.
It should be understood that in one cycle, through the last steps, the minor and major half axes of the fitted elliptical profile of the target flange in the image can be obtained, the roundness value C of the minor and major half axes is obtained, and a plurality of flanges may exist in one image, which is n in number, so s is a total roundness value, and the minimum total roundness value s of each cycle is taken, so that the minimum total roundness value s can ensure that the taken flange edge is closest to the real edge.
Preferably, in the step S8, further includes:
when the calculated number i of the total roundness values S is smaller than the total calculated number M, the calculated number i is increased by 1, the step S3 is returned to by the calculated number i plus 1, the total roundness values S of all the fitted target flange elliptical profiles are calculated again, and if the calculated total roundness values S are smaller than the updated total roundness minimum values S in the last calculation, the calculated total roundness values S are calculated again min The calculated total roundness value s is continuously assigned to the minimum value s of the total roundness min To continue to update the total roundness minimum s min The updated total roundness minimum s will be continued min And in the next calculation of the total roundness value s, the calculated number i is equal to or greater than the total calculated number M.
The total calculation number M is a threshold value of the cycle calculation number, and the present invention is not limited thereto, and may be set by itself according to the need, for example, the total calculation number M may be 255.
The total roundness value s of all fitted target flange elliptical profiles is calculated in a circulating way, and the minimum value s of the total roundness is updated according to the circulating calculation result min Obtaining the final updated total roundness minimum s min Selecting the final updated total roundnessMinimum value s min The corresponding minimum total roundness value s, and the corresponding fitted target flange elliptical profile is obtained according to the minimum total roundness value s, and the following is exemplified:
in the first calculation: total roundness value s=0.9, since total roundness minimum s min The initial value is set to 1,1 > 0.9, and 0.9 is assigned to the total roundness minimum s min At this time, the total roundness minimum s min ＝0.9；
In the second calculation: total roundness value s=0.8, since the updated total roundness minimum s in the first calculation min =0.9, 0.9 > 0.8, assigning 0.8 to the total roundness minimum s min At this time, the total roundness minimum s min ＝0.8；
In the third calculation: total roundness value s=0.7, since the updated total roundness minimum s in the second calculation min = 0.8,0.8 > 0.7, assigning 0.7 to the total roundness minimum s min At this time, the total roundness minimum s min ＝0.7；
In the fourth calculation: total roundness value s=0.8, since the updated total roundness minimum s in the third calculation min =0.7, 0.8 > 0.7, at which time the total roundness minimum s is not updated min Total roundness minimum s min Still 0.7;
......
and so on, until in the ith calculation: total roundness value s=0.5, since the updated total roundness minimum s in the i-1 th calculation min = 0.6,0.6 > 0.5, assigning 0.5 to the total roundness minimum s min At this time, the total roundness minimum s min And (4) selecting a minimum total roundness value s corresponding to the minimum value of the total roundness of the last update of 0.5, and obtaining a corresponding fitted target flange elliptical profile according to the minimum total roundness value of 0.5, namely the fitted target flange elliptical profile aimed at in the ith calculation.
Preferably, in the step S1, further includes: and acquiring a flange image to be identified by adopting a high-definition camera.
Specifically, a device formed by combining a large constant CCD camera and a sea-Kangwei vision lens is selected to collect flange images to be identified, wherein the collected flange images to be identified are 3672 pixels in height and 5496 pixels in width.
The flange identification method based on image processing is applied to the intelligent oil delivery arm, and has higher identification rate and accuracy rate for the flange on the ship.
The present invention is not limited to the above-mentioned embodiments, but is intended to be limited to the following embodiments, and any modifications, equivalents and modifications can be made to the above-mentioned embodiments without departing from the scope of the invention.
Claims (8)
1. The flange identification method based on image processing is characterized by comprising the following steps of:
step S1: acquiring a flange image to be identified;
step S2: processing the flange image to be identified to obtain a processed flange image;
step S3: performing image binarization processing on the processed flange image to obtain a binarized image;
step S4: performing morphological operation on the binarized image to obtain a flange image after morphological operation;
step S5: screening all contours in the flange image after morphological operation to obtain a plurality of target flange contours;
step S6: respectively carrying out ellipse fitting on a plurality of target flange profiles to obtain a plurality of fitted target flange ellipse profiles;
step S7: circularly calculating the total roundness value s of the plurality of fitted target flange elliptical profiles, and setting the minimum value s of the total roundness in advance min Calculating knots from cyclesUpdating the total roundness minimum s min ；
Step S8: judging whether the calculated number i of the total roundness value S is larger than or equal to the total calculated number M, when the calculated number i is smaller than the total calculated number M, adding 1 to the calculated number i, returning to the step S3 by adding 1 to start cyclic calculation of the total roundness value S, and continuously updating the total roundness minimum value S min Until the calculated times i is more than or equal to the calculated times M; when the total calculated number M is greater than or equal to the total roundness minimum value s updated last is selected min The corresponding minimum total roundness value S, the corresponding fitted target flange elliptical profile is obtained according to the minimum total roundness value S, and step S9 is executed;
step S9: displaying the fitted target flange ellipse outline corresponding to the minimum total roundness value s on the flange image to be identified to obtain a flange identification result;
wherein, in the step S7, further includes:
respectively calculating the roundness value of each fitted target flange elliptical contour, and calculating the total roundness value s of the plurality of fitted target flange elliptical contours according to the roundness value of each fitted target flange elliptical contour;
calculating the roundness value of each fitted target flange elliptical profile through the formula c=b/a, wherein a represents the major half axis of the ellipse, b represents the minor half axis of the ellipse, and the calculation formula of the total roundness value s of all fitted target flange elliptical profiles is:
wherein C is 1 ，C 2 ，...，C n Respectively representing the roundness value of each fitted target flange elliptical contour, wherein n represents the number of the determined target flange elliptical contours, and the total roundness value s is not larger than 1 under normal conditions, so that the total roundness minimum value s is obtained min The initial value of (1) is set to be 1, and the currently calculated total roundness value s and the total roundness minimum value s are calculated min In comparison with s min S > s, then assign s to s min To update the total roundness minimum s min 。
2. The flange identification method based on image processing according to claim 1, further comprising, in the step S2:
performing median filtering treatment on the flange image to be identified to obtain a filtered flange image;
and converting the filtered flange image into a gray image.
3. The flange identification method based on image processing according to claim 2, wherein the steps S3 and S4 further comprise:
performing image binarization processing on the gray level image to obtain a binarized image;
and sequentially performing a closing operation and an opening operation on the binarized image to obtain the flange image after morphological operation.
4. The flange identification method based on image processing according to claim 2, further comprising:
judging whether the filtered flange image is a gray image or not;
if the filtered flange image is a color image, the filtered flange image is first grayed, and the graying formula is Gray (i, j) =ar (i, j) +bg (i, j) +cb (i, j), wherein Gray represents a value after graying of a pixel point, R, G, B represents color component values of red, green and blue on the corresponding pixel, a, b and c are weights of red, green and blue respectively, and herein a, b and c are standard values according to the sensitivity degree of human eyes, and are respectively 0.299, 0.578 and 0.114;
and if the filtered flange image is a gray image, directly performing image binarization processing.
5. The flange identification method based on image processing according to claim 1, wherein in the step S3, further comprising:
setting the initial threshold of image binarization as 0, wherein the formula of image binarization is as follows:
where T represents a threshold, the formula for binarizing the image means that pixels above the threshold are set to be brightest and pixels below the threshold are set to be darkest.
6. The flange identification method based on image processing according to claim 1, further comprising, in the step S6:
and respectively carrying out ellipse fitting on a plurality of target flange profiles by adopting a least square method to obtain a plurality of fitted target flange ellipse profiles.
7. The flange identification method based on image processing according to claim 1, further comprising, in the step S8:
when the calculated number i of the total roundness values S is smaller than the total calculated number M, the calculated number i is increased by 1, the step S3 is returned to by the calculated number i plus 1, the total roundness values S of all the fitted target flange elliptical profiles are calculated again, and if the calculated total roundness values S are smaller than the updated total roundness minimum values S in the last calculation, the calculated total roundness values S are calculated again min The calculated total roundness value s is continuously assigned to the minimum value s of the total roundness min To continue to update the total roundness minimum s min The updated total roundness minimum s will be continued min And in the next calculation of the total roundness value s, the calculated number i is equal to or greater than the total calculated number M.
8. The flange identification method based on image processing according to claim 1, wherein in the step S1, further comprising: and acquiring a flange image to be identified by adopting a high-definition camera.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110776870.8A CN113469980B (en) | 2021-07-09 | 2021-07-09 | Flange identification method based on image processing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110776870.8A CN113469980B (en) | 2021-07-09 | 2021-07-09 | Flange identification method based on image processing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113469980A CN113469980A (en) | 2021-10-01 |
| CN113469980B true CN113469980B (en) | 2023-11-21 |
Family
ID=77879460
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110776870.8A Active CN113469980B (en) | 2021-07-09 | 2021-07-09 | Flange identification method based on image processing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113469980B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114485484B (en) * | 2021-11-25 | 2024-05-07 | 郑州郑大智能科技股份有限公司 | Digital detection and correction method for annular workpiece size |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105956600A (en) * | 2016-04-15 | 2016-09-21 | 南京理工大学 | Bolt identification method based on ellipse fitting and SVM under complicated background |
| CN107369140A (en) * | 2017-06-29 | 2017-11-21 | 大连理工大学 | High-accuracy target ball center extraction method under unstructured moving grids |
| CN108734189A (en) * | 2017-04-20 | 2018-11-02 | 天津工业大学 | Vehicle License Plate Recognition System based on atmospherical scattering model and deep learning under thick fog weather |
| WO2019000653A1 (en) * | 2017-06-30 | 2019-01-03 | 清华大学深圳研究生院 | Image target identification method and apparatus |
| CN109843819A (en) * | 2016-09-08 | 2019-06-04 | 康宁股份有限公司 | The product and its manufacturing method in the hole with tool morphological properties |
| CN111161343A (en) * | 2019-12-30 | 2020-05-15 | 芜湖哈特机器人产业技术研究院有限公司 | Water pump orifice ring visual identification method |
| CN111178173A (en) * | 2019-12-14 | 2020-05-19 | 杭州电子科技大学 | Target colony growth characteristic identification method |
| CN112082493A (en) * | 2020-09-03 | 2020-12-15 | 武汉工程大学 | Pipeline flange inner radius visual measurement method based on binocular imaging |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4636146B2 (en) * | 2008-09-05 | 2011-02-23 | ソニー株式会社 | Image processing method, image processing apparatus, program, and image processing system |
| JP6303332B2 (en) * | 2013-08-28 | 2018-04-04 | 富士通株式会社 | Image processing apparatus, image processing method, and image processing program |
| CN107066933B (en) * | 2017-01-25 | 2020-06-05 | 武汉极目智能技术有限公司 | Road sign identification method and system |
-
2021
- 2021-07-09 CN CN202110776870.8A patent/CN113469980B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105956600A (en) * | 2016-04-15 | 2016-09-21 | 南京理工大学 | Bolt identification method based on ellipse fitting and SVM under complicated background |
| CN109843819A (en) * | 2016-09-08 | 2019-06-04 | 康宁股份有限公司 | The product and its manufacturing method in the hole with tool morphological properties |
| CN108734189A (en) * | 2017-04-20 | 2018-11-02 | 天津工业大学 | Vehicle License Plate Recognition System based on atmospherical scattering model and deep learning under thick fog weather |
| CN107369140A (en) * | 2017-06-29 | 2017-11-21 | 大连理工大学 | High-accuracy target ball center extraction method under unstructured moving grids |
| WO2019000653A1 (en) * | 2017-06-30 | 2019-01-03 | 清华大学深圳研究生院 | Image target identification method and apparatus |
| CN111178173A (en) * | 2019-12-14 | 2020-05-19 | 杭州电子科技大学 | Target colony growth characteristic identification method |
| CN111161343A (en) * | 2019-12-30 | 2020-05-15 | 芜湖哈特机器人产业技术研究院有限公司 | Water pump orifice ring visual identification method |
| CN112082493A (en) * | 2020-09-03 | 2020-12-15 | 武汉工程大学 | Pipeline flange inner radius visual measurement method based on binocular imaging |
Non-Patent Citations (3)
| Title |
|---|
| Design of a New Vision-Based Method for the Bolts Looseness Detection in Flange Connections;Chenyu Wang 等;《IEEE Transactions on Industrial Electronics ( Volume: 67, Issue: 2, February 2020)》;全文 * |
| 基于OpenCV的图像椭圆特征识别与定位研究;胡瑞钦;张立建;孟少华;;计算机测量与控制(第12期);全文 * |
| 基于莱特准则的椭圆拟合优化算法;曹俊丽;李居峰;;计算机应用(第01期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113469980A (en) | 2021-10-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US7489345B2 (en) | Image processing apparatus, image-taking system, image processing method and image processing program | |
| JP3679512B2 (en) | Image extraction apparatus and method | |
| CN113766125B (en) | Focusing method and device, electronic equipment and computer readable storage medium | |
| US8917938B2 (en) | Method for estimating blur degree of image and method for evaluating image quality | |
| US5841899A (en) | Specific color field recognition apparatus and method | |
| JP6890427B2 (en) | Car number recognition device | |
| CN110954553B (en) | Lens optical detection system | |
| CN109886958B (en) | Method, device and system for automatically identifying welding seam position based on square tube | |
| CN110930321A (en) | Blue/green screen digital image matting method capable of automatically selecting target area | |
| CN113469980B (en) | Flange identification method based on image processing | |
| CN111192213B (en) | Image defogging self-adaptive parameter calculation method, image defogging method and system | |
| CN109766846B (en) | Video-based self-adaptive multi-lane traffic flow detection method and system | |
| TWI383690B (en) | Method for image processing | |
| CN107644437B (en) | Color cast detection system and method based on blocks | |
| CN116057949B (en) | System and method for quantifying flare in an image | |
| JP2005165387A (en) | Method and device for detecting stripe defective of picture and display device | |
| CN111192280B (en) | Method for detecting optic disc edge based on local feature | |
| CN113408380A (en) | Video image adjusting method, device and storage medium | |
| CN109285151B (en) | AI intelligent dimming method | |
| CN111738934B (en) | Automatic red eye repairing method based on MTCNN | |
| CN110688876A (en) | Lane line detection method and device based on vision | |
| CN114170153A (en) | Wafer defect detection method and device, electronic equipment and storage medium | |
| US20130163862A1 (en) | Image processing method and device for redeye correction | |
| CN113516709B (en) | Flange positioning method based on binocular vision | |
| CN115511833B (en) | Glass surface scratch detecting system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |